MEACAM Reports

The Middle East Anticipatory Climate Action Model (MEACAM) is an online platform that provides geographically disaggregated agricultural drought and flood predictions, and estimates of how many people, communities, and internally displaced person (IDP) camps will be affected by these events. Currently, the platform provides national-level coverage of drought and flooding hazards for Iraq, Syria, and Yemen. MEACAM is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or DG ECHO. Neither the European Union nor the granting authority can be held responsible for them.

Floods in focus

MEACAM research report

April 2025

Floods in Focus provides a high-level overview of flash and river flooding in Iraq, Syria, and Yemen, including recent trends and its impact on displacement. The report contains river flood vulnerability maps, flood-induced displacement trends, and context-specific flood vulnerabilities identified by local key informants. The technical specification of the MEACAM flood prediction model and thresholding approach are also outlined. 

The paper is intended to provide a broad overview of flash and river flooding and its human impact. The paper also identifies areas most vulnerable to river flooding and heavy rainfall, which would benefit the most from the MEACAM platform’s flood predictions to inform an early warning and/or early action. 

Drought in focus

MEACAM research report

April 2025

Drought in Focus’ is the first of four research papers produced by Mercy Corps’ Crisis Analysis for the Middle East Anticipatory Climate Action Model (MEACAM) project. This paper provides a high-level overview of agricultural drought in Iraq, Syria, and Yemen, including recent trends and their impact on displacement. Field interviews were conducted in northeast Syria which provide examples of positive and negative coping mechanisms for agricultural drought in the region. The technical specification of the MEACAM agricultural drought prediction model and thresholding approach taken to identify agricultural drought are also outlined.